Determinants of effect tax rates for firms listed on China s stock markets: panel models with two-sided censors

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1 Determinants of effect tax rates for firms listed on China s stock markets: panel models with two-sided censors Yong-Ching Chiou, Yao-Chih Hsieh Wenyi Lin Feng Chia University, Taiwan Key Words Effective tax rate, two-sided censoring, political power (cost) hypothesis, JEL:C21, C52, H25 Abstract This paper is to investigate the determinants of ETRs (Effective Tax Rate) for the firms listed on China s (Shanghai Shenzen) stock markets. The panel data consists of 360 firms from 2004 to 2011 as our empirical data. Since the dependent variable, ETRs, is left censored at 0 right censored at 1, the estimation for panel data model with twosided censoring suggested by Alan, Honor e, Leth-Petersen (2008) is implemented in this paper. There are two important findings are obtained: first, this model can add more observations especially the observations with tax preferences. Second, theories suggest that ETR reflects outcomes of tax preference this paper is the first time to consider the effective tax rates set between 0 1 this range is more meaningful for the ETRs. Introduction Due to its convenience for measuring the tax burden of a corporate, average effective tax rates (ETRs) have long been used by policy makers interest groups in tax reform debates. Governments provide tax incentives for firms subject to high levels of risk due to large amounts of capital, a lengthy production process or uncertainty in activities such as exploration (Stickney McGee, 1982). Reduction of the corporate tax as a tool for stimulating a certain industry elimination of certain tax preference as a tool for pursuing social justification are also the focus of the tax policy debates. Tax incentives reduce the tax burden of firms imply non-neutrality of the tax system. Proponents of neutrality argue that the market would more effectively price the risk factors faced by some firms. Further, tax burdens varying across firms is sometimes used to suggest that the tax system is inequitable subsequently. Since ETR is defined as the ratio (in percentage) of taxes paid based on a firm s current or total income to its pre-tax accounting income, ETR should be similar for all firms in a country. Therefore, evidence that corporate ETRs vary across firms over time has been used to suggest that the tax system is inequitable, as a justification for a corporate tax reform. In other words, study on the variability of ETRs among firms is a way to check tax neutrality social justification in a country. Variability of ETRs among firms has been recognized in literature. Originated from a serial reports published by the Citizens for Tax Justice (CTJ 1984, 1985, 1986) that the largest United States corporations were not paying their fair share of taxes. Whether the ETRs are systematically related to firm size has been the focus of the tax policy debates literature studies. Theoretically, there are two different hypotheses suggested in literature to explain the relation between firm size level of ETRs. One, the political cost hypothesis, is that the higher visibility of larger more successful firms might be victims of greater regulator actions wealth transfers as a result, incur a political cost in the form of a higher ETR (Zimmerman 1983). Another is that larger firms pay less tax because they devote more efforts to tax planning political lobbying so that the large firms pay their share of tax less. This is referred to as the political power (or clout) hypothesis. Empirically, studies on the relation between ETRs firm size have produced conflicting results. Zimmerman (1983) observes a positive association between ETRs firm size while Porcano (1986) observes a negative association. No association between ETRs firm size is found in Stickney McGee (1982) Shevlin Porter (1992). Subsequent studies have tried to reconcile the conflicting results by using modified proxies, time period, data basis, methodologies(e.g., Gupta 306

2 Newberry,1997; Kern Morris,1992; Wilkie Limberg,1990; Holl, 1998; Kim Limpaphayom, 1998; Derashid Zhang, 2003; Liu Cao, 2007). Panel data models have been used to overcome the problem of model miss-specification in studies on determinants of ETRs (e.g. Gupta Newberry, 1997; Harris Feeny, 2003; Liu Cao, 2007). Besides, Gupta Newberry (1997) suggest that because ETRs concerns firms with tax refunds, negative income measurement issue, they constrained the ETR of their sample firms to lie between zero one. However, the censoring characteristic of ETRs is not considered in existing literature. In our sample, there are more than 28 % of firms with zero ETRs. It is well know that the regression estimators are biased inconsistent if the existence of censoring in dependent variable is neglected. Therefore, this paper attempts to use the panel data models with twosided censoring suggested by Alan, Honor e, Leth-Petersen (2008) to study the determinants of ETRs for the listed on China stock markets. The remaining of this paper is organized as follows. Section 2 introduces the estimation of panel data models with two-sided censoring suggested by Honor e Leth-Petersen (2008). Empirical studies are investigated in section 3. Conclusions are presented in the last section. Panel Data Models with Two-sided Censoring Since the effective tax rates are between 0 1 with a significant number of observations on either of the limits. In panel data setting, the specific model is (1) where is stationary conditional on. The derivation of estimator for β suggested by Alan, Honor e, Leth-Petersen (2008) is briefly summarized as follows. Define, for ma mi so (1) can be written as Consider an individual, i, in two time periods, t s. The distribution of ( ) will be the same as that of except that the former is censored from below at from above at ( ). The dotted line depicts the distribution of, while the solid line gives the distribution of, which typically has point mass at (illustrated by the fatter vertical lines). Since will typically differ from the distributions of (given ( )) will differ even if { } is stationary. However, it is clear that one could obtain identically distributed residuals by artificially censoring from below at max from above at min. One can then form moment conditions from the fact that the difference in these re-censored residuals will be orthogonal to functions of Also define functions,.),.) over the interval (b a) to (b a) as follows,d),d) 307

3 With these definitions,, residuals by artificially censoring from above at min Let the functions ), ) will give the difference in the re-censored max. are defined over the interval (b a) to (b a) as The functions are constructed so their derivatives are respectively. Finally, define R Alan, Honor e, Leth-Petersen (2008) show that R, Suppose that Where are identically distributed rom variables with support on the whole real line. Then Alan, Honor e Leth-Petersen (2008) prove that arg If E is stationary conditional on with support on the whole real line, then the set of solutions to E is Therefore, when the censoring points are a b, the sample analog estimator is where the are exogenous weights is the number of observations for the ith individual. is a trivial choice. It is proved by Alan, Honor e Leth-Petersen (2008) that under appropriately conditions. Under rom sampling is consistent asymptotically normal Where 308

4 With ( Following stard arguments, these are consistently estimated by (1 ) -1 With ( Empirical Studies The sample data used in this study is collected from the Taiwan Economic Journal (TEJ) database. It consists of 360 firms each year listed on China s stock market from 2004 to The ETR is measured as four different ETRs measures are used. We follow the approach used by Porcano (1986), ETR1 is defined as (tax expenses - deferred tax expenses) divided by (profit before interest tax paid) ETR2 is another version of the measure used by Porcano (1986): (tax expenses)/(profit before interest tax). ETR 3 is the measure used by Stickney McGee (1982) is given as (tax expenses)/(pre-tax profit (deferred tax expenses/statutory tax rate)). ETR4 is the measure used by Shevlin (1987) is calculated as (tax expenses deferred tax expenses)/(pre-tax profit (changes in deferred tax/statutory tax rate)). tax expenses divided by profit before interest tax paid. It is worthy to mention that the negative ETRs are replaced with zeros with one for those ones larger than one. There are, totally, 99, 105, firms with zero ETR for definitions of ETR1, ETR2, ETR3 ETR4. For the right censoring, there are 0, 0, 11 6 firms with ETR equal to one in ETR1, ETR2, ETR3, ETR4, respectively. To explore the marginal effect of firm size on ETRs, the following firm-specific characteristics are taken as control variables: leverage (total liabilities divided by total asset value, denoted as LEV ), capital intensity (net fixed assets divided by total assets, denoted as CI ), inventory intensity (inventory divided by total assets, denoted as II ), return on assets (pre-tax profits divided by total assets, denoted as ROA ), firm size (denoted as SIZE ) is measured as the natural logarithm of total asset value. The state ownership variable is defined as the ratio of state-owned shares over total outsting shares denoted as S1. The reasons behind to choose these variables are based on previous studies (e.g., Porcano (1986), Gupta Newberry (1997), Derashid Zhang (2003), Liu Cao (2007)). To account for the factors discussed above, The empirical results are presented in table

5 Table 1 Estimated Results for Panel Data Model with Two-side Censoring ETR1 ETR2 ETR3 INTERCEPT (0.043) (0.039) (0.064) * S1 (0.014) (0.012) (0.022) CI (0.021) (0.019) (0.033) 0.054** 0.070*** 0.121*** II (0.027) (0.025) (0.042) ** * LEV (0.035) (0.032) (0.055) 0.213*** 0.276*** 0.207*** ROA (0.037) (0.034) (0.055) 0.011*** SIZE (0.003) (0.003) (0.004) ETR (0.056) (0.018) (0.027) 0.096*** (0.035) (0.046) 0.162*** (0.044) 0.008** (0.004) The coefficient for S1, government equity, does not appear to be statistically different from zero, except ETR2.This result suggests that the effects of government ownership may lie in areas other than ETR. The coefficient of ln assets, firm size, is positive statistically significant when ETR is measured as ETR1 ETR4. Thus, we can accept the political cost hypothesis when TER is defined as ETR1 ETR4 The coefficient for leverage is negative statistically significant when ETR is measured as ETR1 ETR3. This coefficient is not statistically different from zero under ETR2 ETR4. Thus, there is some evidence to support the intuitive notion that debt financing can be used as a tax shield for China s firms. The coefficient for capital intensity is all statistically insignificant for all ETR measures. This evidence does not support the notion that higher capital investment the resultant higher depreciable costs lead to a lower ETR. This evidence is inconsistent with two previous studies in the U.S. context (Gupta Newberry, 1997; Stickney McGee, 1982). The coefficient for inventory intensity, on the other h, is all statistically different from zero under all ETR measures. The coefficients of ROA, the measure for efficiency in performance is all positive significant when ETR is measured as ETR1, ETR2, ETR3, ETR4. These results suggest that more efficient firms pay more effective tax in China. And these results are consistent to previous studies. Conclusions This paper is to investigate the determinants of ETRs for the firms listed on China s stock markets. This paper adopts two-sided censoring model to China s stock market from 1997 to 2006 as our empirical data. Since the dependent variable, ETRs, is left censored at zero right censored at 1, the estimation for panel data model with two-sided censoring suggested by Honor e Leth-Petersen (2008) is implemented in this paper. Several contributions are obtained: first, this model can add more observations especially the observations with tax preferences. Second, at our best knowledge, this paper is the first time to consider the effective tax rates set between 0 1 this range is more meaningful for the ETRs. References Alan,S., S. Leth-Petersen (2006), Tax incentives Household Portfolios: A Panel Data Analysis, working paper, Center for Applied Microeconometrics, University of Copenhagen. Alan, S., Bo E. Honor e, S. Leth-Petersen (2008), Estimation of Panel Data Models with Two-Sided Censoring, working paper, Department of Economics, Princeton University. Barrodale, I. F. Roberts (1974), Solution of an Overdetermined System of Equations in the ℓ1 Norm, Communications of the ACM, 17, Buijink, W., B. Janssen, Y. Schols (2002), Evidence of the Effect of Domicile on Corporate Effective Tax Rates in the European Union, Journal of International Accounting, Auditing, Taxation, 11, Bofinger, E. (1975), Estimation of A Density Function Using Order Statistics, Australian Journal of Statistics, 17,

6 Callihan, D.S. (1994), Corporate Effective Tax Rates: A Synthesis of the Literature, Journal of Accounting Literature, 13, Chen, M.-C., S. Lin, T.-H. Chang (2001), The Impact of Tax-Exempt Stock L Capital Gains on Corporate Effective Tax Rate, Taiwan Accounting Review, 2, Derashid, Check, Hao Zhang (2003), Effective Tax Rates the Industrial Policy Hypothesis: Evidence from Malaysia, Journal of International Accounting Auditing Taxation, 12, Engle, R. S. Manganelli (1999), CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles, NBER working paper No Fitzenberger, B. (1996), A Guide to Censored Quantile Regressions, In C. Rao, G. Maddala (eds.), Hbook of Statistics, North-Holl: New York. Fitzenberger, B. (1998), The Moving Blocks bootstrap Robust Inference for Linear Least Squares Quantile Regressions, Journal of Econometrics, 82, Fullerton, D. (1984), Whcih Effective Tax Rate?, National Tax Journal, 37, Gupta, S., K. Newberry (1997), Determinants of the Variability of Corporate Effective Tax Rates: Evidence from Longitudinal Data, Journal of Accounting Public Policy, 16, Harris, M. N. S. Feeny (2000), The Determinants of Corporate Effective Tax Rates: Evidence from Australia, Melbourne Institute Working Series, No. 21/99, Melbourne Institute of Applied Economic Social Research, University Melbourne. Harris, M. N. S. Feeny (2003), Habit Persistence in Effect Tax Rates, Applied Economics, 35, Hall, P. S. J. Sheather (1988), On the distribution of a studentised quantile, Journal of Royal Statistical Society, B50, Holl, K. (1998), Accounting Policy Choice: The Relationship Between Corporate Tax Burdens Company Size, Journal of Business Finance Accounting, 25, Huang, G., M. Song (2004), The Determinants of Capital Structure: Evidence from China, Quarterly Economic Journal, 2, Janssen, B., W. Buijink (2000), Determinants of the Variability of Corporate Effective Tax Rates (ETRs): Evidence for the Netherls, Management Administration Research Center (MARC) working paper. Jureˇckov a, J. B. Proch azka (1993), Regression Quantiles Trimmed Least Squares Estimators in Nonlinear Regression Models, Journal of Nonparametric Statistics, 3, Kim, K.A., P. Limpaphayom (1998), Tax Firm Size in Pacific-Basin Emerging Economies, Journal of International Accounting Auditing Taxation, 7, Kern, B. B. M. H. Morris (1992), Taxes Firm Size: The Effect of Tax Legistration during the 1980s, Journal of the American Taxation Association, 14, Koenker, R. G. Bassett (1978), Regression Quantiles, Econometrica, 46, Koenker, R. V. d Orey (1987), Computing Regression Quantiles, Statistical Algorithms, Koenker, R. B.J. Park (1996), An Interior Point Algorithm for Nonlinear Quantile Regression, Journal of Econometrics, 71, Koenker, R., Ng, P. S. Portnoy (1997), Quantile Smoothing Splines, Biometrika, 81, Liu, Xing (2000), Positive Research on Determinants of Financing of Listed Companies in China, In Frontiers Research of Capital Market in China. Beijing: Social Science Literature Press, Liu, Xing Shujun Cao (2007), Determinants of Corporate Effective Tax Rates Evidence from Listed Companies in China, The Chinese Economy, 40, MacKie-Mason, Jeffrey K. (1990), Do Taxes Affect Corporate Financing Decisions? Journal of Finance, 45, Manzon, G., W.R. Smith (1994), The Effect of the Economic Recovery Tax Act of 1981 the Tax Reform Act of 1986 on the Distribution of Effective Tax Rates, Journal of Accounting Public Policy, 13, Plesko, George (2003), An Evaluation of Alternative Measures of Corporate Tax Rate, Journal of Accounting Economics, 35, Porcano, T. (1986), Corporate Tax Rates: Progressive, Proportional, or Regressive, Journal of Accounting Public Policy, 7, Powell, J.L. (1984), Least Absolute Deviations Estimation for the Censored Regression Model, Journal of Econometrics, 25, Powell, J.L. (1986), Censored Regression Quantiles, Journal of Econometrics, 32, Shelvin, T., S. Porter (1992), The Corporate Tax Comeback in 1987: Some Further Evidence, Journal of American Taxation Association, 14, Si, Donghui (2003), Equity Competition in Transform Research: Evidence from Listed Companies in China, Economic Research, 8, Siegfried, J. (1974), Effective Average U.S. Corporate Income Tax Rates, National Tax Journal, 27,

7 Stickney, C., V. McGee (1982), Effective Corporate Tax Rates: The Effect of Size, Capital Intensity, Leverage, Other Factors, Journal of Accounting Public Policy, 1, Taylor, J.W. (2000), A Quantile Regression Neural Network Approach to Estimating the Conditional Density of Multiperiod Returns, Journal of Forecasting, 19, Wang, Fang (1999), A Study on the Income Tax Burden of Listed Companies in China, Economic Research, 5, Wang, Liyan, Xiangqian Liu (2004), IPO the Non-Statutory Tax Preference, Quarterly Economic Journal, 2, Wang, Yanming (2003), The Relations Between Income Tax Burden Size, Area, Industry, Guide to Securities Market, 3, Wilkie, P. (1988), Corporate Average Effective Tax Rates Inferences About the Relative Tax Preference, Journal of the American Taxation Association, 10, Wilkie, P.J., S.T. Limberg (1990), The Relationship Between Firm Size Effective Tax Rate: A Reconciliation of Zimmerman (1983) Porcano (1986), Journal of American Taxation Association, 11, Yang, Zhigang, Ding Ling, Bingzhen Wu (2000), Positive Research on Value Added Tax Income Tax, Economic Research, 12, Zimmerman, J. (1983), Tax Firm Size, Journal of Accounting Economics, 312